Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 23
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Showing 1781 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Network Discovery Software | JDisc DiscoveryJDisc Discovery is a comprehensive network inventory and IT asset management solution designed to help organizations gain clear, up-to-date visibility into their IT environment. It automatically scans and maps devices across the network, including servers, workstations, virtual machines, and network hardware, to create a detailed inventory of all connected assets. This includes critical information such as hardware configurations, software installations, patch levels, and relationshipots between devices.
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ToogleBox: Simplify, Automate and Improve Google Workspace FunctionalitiesToogleBox was created as a solution to address the challenges faced by Google Workspace Super Admins. We developed a premium and secure Software-as-a-Service (SaaS) product completely based on specific customer needs. ToogleBox automates most of the manual processes when working with Google Workspace functionalities and includes additional features to improve the administrator experience.
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LeWorldModel
Official code base for LeWorldModel: Stable End-to-End Joint-Embedding
...It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration files, allowing users to tailor behavior, keybindings, and layouts to their preferences. le-wm is intended for users who prefer keyboard-driven workflows and a distraction-free desktop environment. Its architecture avoids unnecessary complexity, making it easy to understand, modify, and extend. -
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Biomni
Biomni: a general-purpose biomedical AI agent
Biomni is a general-purpose biomedical AI agent designed to autonomously perform complex research tasks across a wide range of scientific domains, combining language model reasoning with structured planning and execution. It integrates retrieval-augmented generation with code-based execution, allowing it to access external knowledge, process data, and generate testable hypotheses in scientific workflows. The system is built to support researchers by automating repetitive and time-consuming tasks such as literature review, data analysis, and experimental design. Biomni operates within a comprehensive environment that includes tools, APIs, and datasets, enabling it to execute multi-step research processes rather than just generating text responses. ... -
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RL with PyTorch
Clean, Robust, and Unified PyTorch implementation
...The project focuses on helping developers and researchers understand reinforcement learning methods by providing clean and reproducible implementations of well-known algorithms. It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL approaches. The repository is structured so that users can easily experiment with different algorithms and training environments. Many examples demonstrate how agents learn to interact with simulated environments through trial and error using reinforcement learning principles. ... -
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Data Science Articles from CodeCut
Collection of useful data science topics along with articles
...The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by data scientists. Each topic often includes references to code repositories, demonstrations, and video tutorials that show how the tools can be applied in real projects. The repository is intended to help practitioners stay updated with current best practices and technologies in the field of data science. -
DataImpulse - Ethical Provider of Residential, Mobile, and Data Center IPsDataImpulse (dataimpulse.com) is a proxy provider offering a pool of over 90 million ethically sourced residential, mobile, and data center IP addresses from 195 countries. Pricing for residential proxies starts at $1 per GB with a pay-as-you-go model; there are no subscriptions or traffic expiration dates.
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NullClaw
Fastest, smallest, and fully autonomous AI assistant infrastructure
...Despite its size, it delivers a complete AI stack with 22+ model providers, 18+ communication channels, integrated tools, hybrid memory, and sandboxed runtime support. Its architecture is fully modular, using vtable interfaces that allow providers, channels, tools, memory backends, and runtimes to be swapped without code changes. NullClaw is secure by design, enforcing pairing-based authentication, strict sandboxing, encrypted secrets, resource limits, and workspace scoping by default. Designed for portability and independence, it supports OpenAI-compatible APIs, multiple tunnels, hardware peripherals, and edge deployments including WASM-based logic. -
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Stagehand
An AI web browsing framework focused on simplicity and extensibility
...Each Stagehand function takes in an atomic instruction, such as act("click the login button") or extract("find the red shoes"), generates the appropriate Playwright code to accomplish that instruction, and executes it. -
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Optax
Optax is a gradient processing and optimization library for JAX
...We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize readability and structuring code to match standard equations, over code reuse. -
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms of its impact on people – i.e., in terms of harm. Fairness of AI systems is about more than simply running lines of code. ... -
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PPTAgent
PPTAgent: Generating and Evaluating Presentations
PPTAgent is a research system for generating and evaluating slide decks that goes beyond simple text-to-slides. It follows a two-stage, edit-based workflow: first it analyzes reference presentations to infer slide roles and structure, then it drafts an outline and iteratively performs editing actions to produce new slides. The project includes both the generation agent and an evaluation framework, PPTEval, to score content quality, design, and coherence. The repository highlights the EMNLP... -
Streamline Hiring with Skill AssessmentsCanditech offers innovative, cheat-proof skill assessments and job simulations to transform your hiring process. From technical skills to soft skills, we help you assess candidates on actual job performance. With over 500 customizable tests and powerful video interview features, you can evaluate real-world capabilities, streamline your hiring, and reduce biases. Whether you’re hiring for remote roles, mass hiring, or looking to expand your diversity pool, Canditech’s data-driven platform ensures the right candidates are chosen for the job every time.
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iFlow CLI
iFlow cli is a comprehensive command-line intelligence
...It supports multiple models and configurable APIs, enabling flexibility in how intelligence is applied to tasks. The system is capable of automating repetitive processes, accelerating development cycles, and reducing manual effort in code analysis and execution. It also integrates with CI/CD pipelines through GitHub Actions, extending its functionality into automated workflows. -
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Watermark-Removal
Machine learning image inpainting task that removes watermarks
...Through these techniques, the model learns to identify regions of the image affected by the watermark and generate realistic replacements for the missing visual information. The repository contains code for preprocessing images, training the model, and running inference on images to automatically remove watermark artifacts. -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ... -
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Quadratic
Data science spreadsheet with Python & SQL
...This makes our grids completely portable and very easy to share. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. Quickly write code and see the output in full detail. No more squinting into a tiny terminal to see your data output. -
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PML
The easiest way to use deep metric learning in your application
This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you... -
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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SentenceTransformers
Multilingual sentence & image embeddings with BERT
...The framework is based on PyTorch and Transformers and offers a large collection of pre-trained models tuned for various tasks. Further, it is easy to fine-tune your own models. Our models are evaluated extensively and achieve state-of-the-art performance on various tasks. Further, the code is tuned to provide the highest possible speed. -
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Framelink MCP for Figma
MCP server enabling AI coding tools to access Figma design data
...Developers can integrate the server with compatible tools such as AI-assisted IDE environments that support MCP-based integrations. When a developer provides a Figma file, frame, or element reference, the AI client can request design data from the server and generate code based on that structure. -
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FLAML
A fast library for AutoML and tuning
...Users can find their desired customizability from a smooth range: minimal customization (computational resource budget), medium customization (e.g., scikit-style learner, search space, and metric), or full customization (arbitrary training and evaluation code). It supports fast automatic tuning, capable of handling complex constraints/guidance/early stopping. FLAML is powered by a new, cost-effective hyperparameter optimization and learner selection method invented by Microsoft Research. -
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freenom
Freenom domain name renews automatically
Freenom domain name automatic renewal. -
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HybridClaw
The enterprise operating layer for open agents
HybridClaw is an emerging open-source framework focused on enabling hybrid AI agent systems that combine local execution, tool integration, and multi-agent orchestration into a cohesive development environment. It is designed to work alongside modern agent ecosystems such as OpenClaw, Claude Code, and similar agentic coding tools, providing a flexible infrastructure for managing agent behaviors, workflows, and capabilities. The project emphasizes modularity, allowing developers to define and compose “skills” or capabilities that agents can invoke dynamically, enabling more adaptive and context-aware automation. HybridClaw aims to bridge the gap between isolated AI tools and fully orchestrated agent systems by enabling communication, coordination, and shared context across multiple agents or processes. ... -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
...It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and attention dimensions. Because it stays close to vanilla PyTorch, you can integrate custom datasets and training loops without framework lock-in. It’s widely used as an educational reference for people learning transformers in vision and as a lightweight baseline for research prototypes. ... -
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Bifrost
The Fastest LLM Gateway with built in OTel observability
...It abstracts away the complexity of working directly with multiple backend providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, etc.), enabling you to plug in providers and switch between them without touching your client code. It is built to be high performance: in benchmark tests at 5,000 requests per second, it reportedly adds only microseconds of overhead and achieves perfect success rates with no failed requests. Bifrost supports features such as automatic fallback (failover between providers), load balancing across API keys/providers, and semantic caching to reduce latency and cost. ... -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
...The model is intended to be competitive with closed-source image generation systems, aiming for high fidelity, prompt adherence, fine detail, and even “world knowledge” reasoning (i.e. leveraging context, semantics, or common sense in generation). The GitHub repo includes code, scripts, model loading instructions, inference utilities, prompt handling, and integration with standard ML tooling (e.g. Hugging Face / Transformers). -
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Xorbits Inference
Replace OpenAI GPT with another LLM in your app
Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop. Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. -
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
...Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code, hyperparameters, launch commands, input data, and resulting model weights. Set wandb.config once at the beginning of your script to save your hyperparameters, input settings (like dataset name or model type), and any other independent variables for your experiments. This is useful for analyzing your experiments and reproducing your work in the future. ...
